Adaptive Contextual Instruction Tool for Online Services
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Solution Overview
Problem
Users often struggle to engage with online services due to unfamiliarity with new features, leading to decreased usage and retention, as traditional methods like documentation and landing page notifications are cumbersome and often ignored.
Innovation Solution
An adaptive contextual learning tool that provides instruction on using features within the context of user interactions, utilizing machine learning to determine effective variants for teaching users how to use online service features by analyzing user interactions and contexts, and tailoring tutorials based on user categories and feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive documentation is provided to teach users about new features, then users gain complete information about feature usage, but users spend excessive time reviewing documentation and may ignore it entirely
Solution Approach 1:
The patent segments comprehensive documentation into small, contextualized information units that are delivered incrementally based on user interactions. Instead of presenting all feature information at once through documentation, the system divides information into discrete tips and guidance elements that appear contextually during feature usage, reducing the time users must dedicate to learning while ensuring complete information delivery.
Solution Approach 2:
The patent applies preliminary action by providing instructional information before users need it, based on predicted user needs and interaction patterns. The system analyzes user behavior and delivers relevant feature information in advance of when users might encounter difficulties, allowing users to learn about features naturally during their workflow rather than spending dedicated time studying documentation.
2Loss of information
If landing page notifications are used to inform users about new features, then users receive information about feature updates, but users often ignore these notifications and do not understand how features help them
Solution Approach 1:
The patent applies local quality by delivering feature information specifically at the location where users interact with features, rather than through generic landing page notifications. Contextual tips and guidance appear directly within the feature interface or workflow area, providing localized information that is immediately relevant to the user's current task and more likely to be understood and acted upon.
Solution Approach 2:
The patent introduces an intermediary layer between feature announcements and users - the contextual instruction system that translates generic feature notifications into personalized, situation-specific guidance. This intermediary analyzes user context, behavior, and preferences to transform standard announcements into tailored tips that explain how features specifically help each user in their current workflow.
3Adaptability or versatility
If the online service continuously enriches and expands feature sets, then the service becomes more helpful and offers more reasons for user engagement, but teaching users about new features becomes increasingly difficult
Solution Approach 1:
The patent applies dynamics by making the instruction delivery system adaptive and responsive to user behavior patterns. As users interact with new features and the service evolves, the system dynamically adjusts the type, timing, and content of instructional tips provided. The instruction complexity and style change based on user proficiency, interaction history, and contextual cues, allowing the system to scale instruction delivery alongside feature expansion without increasing perceived complexity for users.
Solution Approach 2:
The patent implements self-service by enabling the system to automatically analyze user interactions and deliver appropriate instructional content without requiring manual intervention. The contextual instruction system monitors user behavior, identifies when and what features users need help with, and autonomously provides relevant tips and guidance, reducing the burden on users to seek out information while managing the complexity of instruction delivery across expanding feature sets.
Data Source
AI summary
A system and method for increasing user engagement with an online service. The system includes a contextual instruction tool that teaches users about features of the online service. The system provides instruction according to different contexts of a user's interaction on their device. The instructions to the user may be in near-real time to the interaction or sometime after the interaction.